Investigating the Effects of Increased Thermal Generation by Unit Commitment Optimization in Hydrothermal Power Systems Using Lagrange Algorithm

Abstract

Optimization assists power utility in operating the system conveniently, meeting customer’s load demand, reducing peak load consumption, and minimizing transmission system losses. It involves determining the best operating levels for electric power plants to meet the needs of a given network. This paper aims to present an optimization analysis of the economic distribution of generated electricity among the various generation units to meet load demand at the minimum possible cost using the Economic Load Dispatched. Nigerian existing hydrothermal network (a deregulated system in 2013) along with the newly added unit (Olorunsogo thermal unit) was used as the case study.  The obtained data from Nigerian power utility were processed via MATLAB to generate the Quadratic Cost Function (QCF) used to model the generator to get the Cost Coefficients. The Lagrange algorithm developed was also applied to the data using MATLAB to have Dynamic Load Scheduling (DLS) for both hydro and thermal plants. The results indicate cost reduction which enhanced the overall performance and reliability of the system. Observation shows that the newly added thermal unit (Olorunsogo Unit) is efficient and cost-effectively operating. Results also show that hydro plants were allocated high loads, and the system’s smooth operation would require bringing the old thermal units such as Afam, Calabar, Egbin, and Sapele plants online to enhance an improvement in generation demand. Other thermal plants like AES, Delta, and Okapi run at lower power implying their uneconomical unit operation implying their uneconomical unit operation